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      <a href="https://genforce.github.io/" target="_blank"><img src="./assets/genforce.png"></a>
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    <div class="title", style="padding-top: 25pt;">
      Image Processing Using Multi-Code GAN Prior
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  <div class="author">
    <a href="http://www.jasongt.com" target="_blank">Jinjin Gu</a><sup>1</sup>&nbsp;
    <a href="http://shenyujun.github.io" target="_blank">Yujun Shen</a><sup>2</sup>&nbsp;
    <a href="http://bzhou.ie.cuhk.edu.hk" target="_blank">Bolei Zhou</a><sup>2</sup>&nbsp;
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  <div class="institution">
    <sup>1</sup>The Chinese University of Hong Kong, Shenzhen<br>
    <sup>2</sup>The Chinese University of Hong Kong
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  <div class="link">
    <a href="https://arxiv.org/pdf/1912.07116.pdf" target="_blank">[Paper]</a>&nbsp;
    <a href="https://github.com/genforce/mganprior" target="_blank">[Code]</a>
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  <div class="title">Overview</div>
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    We propose multi-code GAN prior (mGANprior) to incorporate the well-trained GANs as effective prior to a variety of image processing tasks. In particular, we employ multiple latent codes to invert a fixed GAN model, and then
    introduce adaptive channel importance to compose the features maps from these codes at some intermediate layer of
    the generator. The resulting high-fidelity image reconstruction enables the trained GAN models as prior to many real-world applications, such as image colorization, super-resolution, image inpainting, and semantic manipulation.
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  <div class="title">Results</div>
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    Various image processing tasks with mGANprior.

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  <div class="bibtex">BibTeX</div>
<pre>
@inproceedings{gu2020image,
  title     = {Image Processing Using Multi-Code GAN Prior},
  author    = {Gu, Jinjin and Shen, Yujun and Zhou, Bolei},
  booktitle = {CVPR},
  year      = {2020}
}
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  <div class="ref">Related Work</div>
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    <div class="comment">
      <a href="https://genforce.github.io/interfacegan/" target="_blank">
        Y. Shen, J. Gu, X. Tang, B. Zhou.
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      <b>Comment:</b>
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      <a href="https://gandissect.csail.mit.edu/" target="_blank">
        D. Bau, J. Y. Zhu, H. Strobelt, B. Zhou, J. B. Tenenbaum, W. T. Freeman, A. Torralba.
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      <a href="https://debug-ml-iclr2019.github.io/cameraready/DebugML-19_paper_18.pdf" target="_blank">
        D. Bau, J. Y. Zhu, J. Wulff, W. Peebles, H. Strobelt, B. Zhou, A. Torralba.
        Inverting layers of a large generator.
        ICLRW 2019.</a><br>
      <b>Comment:</b>
      Inverts GANs by layer-wise Encoder Networks.
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  <div class="citation">
    <div class="image"><img src="./assets/dip.jpg"></div>
    <div class="comment">
      <a href="https://dmitryulyanov.github.io/deep_image_prior" target="_blank">
        D. Ulyanov, A. Vedaldi, V. Lempitsky.
        Deep Image Prior.
        CVPR 2018.</a><br>
      <b>Comment:</b>
      Uses deep neural networks (discriminative model) as structured image prior.
    </div>
  </div>
  <div class="citation">
    <div class="image"><img src="./assets/igan.jpg"></div>
    <div class="comment">
      <a href="http://efrosgans.eecs.berkeley.edu/iGAN/" target="_blank">
        J. Y. Zhu, P. Krähenbühl, E. Shechtman, Alexei A. Efros.
        Generative Visual Manipulation on the Natural Image Manifold.
        ECCV 2016.</a><br>
      <b>Comment:</b>
      Manipulates images by learning the natural image manifold from GANs.
    </div>
  </div>
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